code: def run_graph_conv(self, dtype="float32"):
      num_nodes = 5
  
      edges = [(0, 1), (1, 2), (3, 4)]
      nfeat = np.random.randn(num_nodes, global_feat_dim).astype(dtype)
      efeat = np.random.randn(len(edges), global_feat_dim).astype(dtype)
      weight = np.random.randn(len(edges), global_feat_dim).astype(
          dtype
      )
  
      g = pgl.Graph(
          edges=edges,
          num_nodes=num_nodes,
          node_feat={"nfeat": nfeat},
          edge_feat={"efeat": efeat, "weight": weight},
      )
      pg = g.tensor()
      # feat = paddle.to_tensor(nfeat)
      feat = g.node_feat["nfeat"]
      for conv in get_conv_list():
          out = conv(pg, feat)
          self.assertTrue(isinstance(out, paddle.Tensor))
  
file_path: PGL/tests/test_conv.py
imports: import unittest
  import numpy
  import paddle
  import pgl
label_desc: Use image node_id 1 for calling the ConvTest obj's underlying member method code with example usage: obj.run_graph_conv(dtype) without return types